77,95 €
77,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
39 °P sammeln
77,95 €
77,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
39 °P sammeln
Als Download kaufen
77,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
39 °P sammeln
Jetzt verschenken
77,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
39 °P sammeln
  • Format: ePub

An increasing number of hydrological datasets from earth observations, hydrological models and seasonal forecasts have become available for water managers, consultants and the general public. These datasets are state-of-the-art products which are usually accessible online and may contribute to develop hydrological studies and support water resources management. However, the added value of these datasets has not been completely explored in decision-making processes. Research studies have assessed how well data can help in predicting climate, but there is a lack of knowledge on how well data can…mehr

Produktbeschreibung
An increasing number of hydrological datasets from earth observations, hydrological models and seasonal forecasts have become available for water managers, consultants and the general public. These datasets are state-of-the-art products which are usually accessible online and may contribute to develop hydrological studies and support water resources management. However, the added value of these datasets has not been completely explored in decision-making processes. Research studies have assessed how well data can help in predicting climate, but there is a lack of knowledge on how well data can help in water allocation decisions. This work provides numerical tools, methods and results to evaluate the value of using hydrological datasets to support water allocation decisions at river basin and irrigation district scale. An integrated approach is used to predict climate, improve decisions and reduce negative impacts. Results show that investing in hydrological data with finer spatial and temporal resolution and longer periods of record improves water allocation decisions and reduces agricultural production loss in large irrigation schemes. Using river discharge data from hydrological models and global precipitation enhances irrigation area planning when little in-situ data is available. Moreover, using seasonal streamflow forecasts improves available water estimates resulting in better water allocation decisions. The framework was tested in Costa Rica, Colombia and Australia, but can be applied in any case study around the world.


Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Alexander José Kaune Schmidt was born in Germany, raised in Costa Rica and currently working as a consultant in a Dutch company with special interest in developing projects in Costa Rica. He is an Agricultural Engineer with an MSc degree in Hydraulic Engineering, and over ten years of work experience in water and agriculture projects in the commercial, government, and research sector in the Netherlands, Costa Rica, Colombia, Angola, Georgia, Iran and Australia. Alexander also has experience in consultancy and research projects for hydrological assessment, biomass growth evaluation, and irrigation advice using ground data, numerical tools and remote sensing. He is skilled in project management, valuation methods, simulation models and risk assessment, and passionate about solving problems related to climate change, water supply, food and fibre production and irrigation system operation and planning.